The present disclosure herein relates to a neuromorphic arithmetic device, and more particularly to, a neuromorphic arithmetic device implemented in an analog manner.
A neuromorphic arithmetic device represents a device which mimics the human nervous system or brain to process information. Unlike a structure in which an arithmetic unit, an instruction processor, and a storage unit are independently present and on which a typical computer central processing unit is based, the neuromorphic arithmetic device may process information in parallel. Even while processing information, the neuromorphic arithmetic device may process information with a focus on a newly occurring event.
The neuromorphic arithmetic device may be defined by a two-dimensional or three-dimensional connection of a plurality of neurons. Each neuron may be configured with circuits corresponding to axon, dendrite, and soma in the same manner as constituent elements of a biological neuron. In particular, an arithmetic operation is performed in a synapse circuit connecting neurons.
The role of a synapse circuit (arithmetic unit) is very important to process, quickly and in parallel, information input to the neuromorphic arithmetic device. To quickly process massive data, a typical neuromorphic arithmetic device is provided with an arithmetic unit implemented in a digital manner. According to this configuration, as the amount of data to be processed increases, power consumption and a chip area increase. Therefore, extension of a circuit is limited in an application field in which power consumption is an issue.
In general, in a synapse of an analog neuromorphic arithmetic device, a capacitance of a metal line generated to implement a dendrite is used. Here, addition and multiplication operations are performed by directly charging or discharging a corresponding node by operating an oscillator. However, according to operations performed in this manner, since a metal line having a very high capacitance is directly charged or discharged using an oscillator, the amount of wasted charges is very large when an operating frequency is high, and thus power consumption increases. Furthermore, as the number of synapse circuits increases, the capacitance of a metal line increases, and thus the size of a current source of a synapse is required to be increased to generate the same frequency.